ENGLISH

A Stochastic Grammar of Images

By David Mumford , Song-Chun Zhu

Book information

Publisher
Now Publishers Inc
Year
2007
ISBN
1601980604, 9781601980601, 9781601980618
DOI
10.1561/0600000018
Open Library ID
OL12553918M
Language
english
Format
PDF
Filesize
2 MB (1783165 bytes)
Pages
119\119
Library
avaxhome.ws
Time added
2010-05-31 15:29:46

Description

A Stochastic Grammar of Images is the first book to provide a foundational review and perspective of grammatical approaches to computer vision. In its quest for a stochastic and context sensitive grammar of images, it is intended to serve as a unified frame-work of representation, learning, and recognition for a large number of object categories. It starts out by addressing the historic trends in the area and overviewing the main concepts: such as the and-or graph, the parse graph, the dictionary and goes on to learning issues, semantic gaps between symbols and pixels, dataset for learning and algorithms. The proposal grammar presented integrates three prominent representations in the literature: stochastic grammars for composition, Markov (or graphical) models for contexts, and sparse coding with primitives (wavelets). It also combines the structure-based and appearance based methods in the vision literature. At the end of the review, three case studies are presented to illustrate the proposed grammar. A Stochastic Grammar of Images is an important contribution to the literature on structured statistical models in computer vision.

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